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Background: Multiple myeloma (MM) is a blood cancer type affecting plasma cell in bone marrow. MM is heterogenous in nature but t(11;14)(q13;q32) translocation is a common prognostic marker among MM patients. One of the most frequent oncogenic drivers involved in this chromosomal rearrangement is CCND1 (Cyclin D1) gene translocation downstream to the immunoglobulin heavy chain (IGH), which results on overexpression of CCND1, thus promoting abnormal cell proliferation. Oncogenic CCND1 RNA levels can result from translocations such as t(11;14), gene amplifications, increased transcription rates and/or RNA stability. Indeed, CCND1 RNA overexpression has a favorable prognostic value for patients treated with high doses of chemotherapies but important challenges remain in accurate detection of CCND1 RNA levels. Currently, FISH is the gold standard method for detecting t(11:14) translocations at the DNA level. However, it cannot detect CCND1 overexpression. Therefore, a method that can detect CCND1 overexpression levels, as well as in frame transcripts has clinical implications. In the current study we leveraged in-use NeoGenomics Heme TNA single tube NGS assay to enable the detection of CCND1 RNA overexpression as a complementary test to FISH testing. Methods: We performed RNA sequencing from 32 healthy donors and on fixed cell pellets from 94 CD138-enriched BM samples from MM patients and from using the amplicon based (Qiagen, inc) NGS assay. We developed pipeline for gene expression by TPM count (transcript per million) for CCND1, and further normalized to the "housekeeping" gene GUSB. We validated the normalization to GUSB by comparing to normalization using the geometric mean of four housekeeping genes (GUSB, PGD, RPL5 and RPL19) showing a high correlation (R 2>0.95). A commercially available qRT-PCR assay was used as orthogonal method to further confirm the linearity of the quantitative gene expression signal in NGS. The analytical cutoff was determined from normalized TPM calculation from 32 healthy volunteers following CLSI guideline (CLSI_EP17-A2) and further updated from MM-PCE samples with t(11:14) translocations from a CLIS-validated FISH assay . Results: From 94 CD138-enriched BM samples, 26 had t(11:14) translocations, or CCND1 gains as detected by FISH, 15 samples were confirmed negative by FISH and 32 normal volunteers with no suspected disease. Also, we determined the analytical cutoff for CCND1 overexpression based on the CLSI guidelines to be 2.37 times the expression level of GUSB ("housekeeping" gene) using normal volunteers (n=32) (sensitivity 86% and specificity 77%). We found specificity to be low, so further evaluated the threshold using a ROC curve analysis with multiple tests. Using Fischer's exact test, we found CCND1 expression 3.27 times the GUSB expression to yield higher specificity of 86.5 % and sensitivity for 78.9%. Further, we used 26 FISH positive and 32 normal samples to build a new model and determined the cutoff for CCND1 overexpression to be 4.15 times GUSB expression, which resulted lower sensitivity but higher specificity (75% sensitivity and 100% specificity). When we evaluated 15 FISH negative samples with this cutoff we observed CCND1 was not overexpressed in six samples, but 9 samples did have some degree of overexpression. Overexpression was confirmed by qRT-PCR. Two CCND1 high- and low- expressing normal samples (MM-PCE 27 and 48) were further evaluated using alternative extraction methods to test the dependencies on extractions and the data showed concordant to each other for overexpression. Interestingly, 1 sample (MM-PCE-27) showed very high overexpression without t(11:14) translocation event (~100 fold over expressed). Cytogenetic studies were discordant with FISH as well for this sample, showing abnormalities related to chr7q,13q,12p but no indication of any chr11 related event. Conclusions: In this study we evaluated our existing NGS assay for CCND1 overexpression using TNA as a surrogate for traditional FISH, while demonstrating the accuracy of the RNA quantitation by NGS using qRT-PCR. We developed an RNA-seq based CCND1 expression assay that could be used to complement traditional FISH testing especially if there is limited specimen. The confirmation of overexpression in FISH negative samples may suggest new ways to improve MM patients risk stratification and treatment. Disclosures Ghosal: NeoGenomics Laboratories: Current Employment. Alarcon: NeoGenomics Laboratories: Current Employment. Koo: Neo Genomics Laboratories: Current Employment. Kang: Neo Genomics Laboratories: Current Employment. Ramesh: Neo Genomics Laboratories: Current Employment. Gyuris: Neo Genomics Laboratories: Current Employment. Jung: NeoGenomics Laboratories, Inc.: Current Employment. Thomas: NeoGenomics Laboratories, Inc.: Current Employment. Fabunan: NeoGenomics Laboratories, Inc.: Current Employment. Magnan: NeoGenomics Laboratories, Inc.: Current Employment. Nam: NeoGenomics Laboratories, Inc.: Current Employment. Petersen: Neo Genomics Laboratories: Current Employment. Lopez-Diaz: NeoGenomics Laboratories, Inc.: Current Employment. Yamahata: Neo Genomics Laboratories: Current Employment. Bender: NeoGenomics Laboratories, Inc.: Current Employment. Agersborg: NeoGenomics Laboratories, Inc.: Current Employment. Ye: Neo Genomics Laboratories: Current Employment. Funari: NeoGenomics Laboratories, Inc.: Current Employment.

Background: Acute Lymphocytic Leukemia (ALL) is the most common childhood cancer and accounts for about a quarter of adult acute leukemias. Current NCCN recommendations for clinical testing for risk stratification and treatment guidance include karyotyping, FISH testing for translocations, and RT-PCR for gene fusions and sequencing for DNA mutations detection. Most NGS based approaches test DNA mutations and RNA fusions separately, thereby requiring higher input material and multiple workflows adding to the cost and turn-around-time. An NGS based assay for the detection of DNA variants (NeoGenomics Heme NGS assay) in heme malignancies using Total Nucleic Acid (TNA) is already available in our clinical laboratory and complements FISH based fusion detection and karyotyping but an integral assay to detect both DNA and RNA alterations with a simple workflow for ALL is needed. Methods: We used TNA or RNA spiked-in with DNA to simulate TNA samples, extracted from 93 bone marrow and peripheral blood samples from patients and healthy donors, along with commercial fusion reference myeloid samples Seraseq Myeloid Fusion RNA Mix (SeraCare Inc.) controls. DNA/RNA libraries were prepared using a custom amplicon based Multimodal NGS panel (Qiagen Inc.) targeting 297 genes and 213 genes (select exons) for DNA and RNA fusion detection, respectively. The enriched dual indexed amplicon libraries were sequenced on an Illumina NovaSeq 6000. The sequence data was processed with a customized bioinformatic pipeline for DNA variant as well as a novel machine learning algorithm for RNA fusion detection. We analyzed sensitivity, specificity, accuracy, reproducibility, and repeatability for clinical use. The DNA variants were orthogonally confirmed using other NGS assays, and the RNA fusions were confirmed on an RNA-seq Archer assay or RT-Sanger confirmation assays. Results: Here, we developed and validated a single tube comprehensive NGS panel using a custom multimodal chemistry that uses TNA as input for simultaneous dual detection of DNA and RNA abnormalities in ALL patients' samples. We performed the analytical validation of our Heme NGS assay for the RNA panel to detect fusions in ALL, using TNA input for comprehensive DNA and RNA mutation detection. The fusion concordance was 95% for the RNA fusion panel. The assay detected BCR-ABL1 (7/7), ETV6-RUNX1 (1/1), KMT2A fusions (4/5), TCF3-PBX1 (1/1), and PCM1-JAK2(1/1). The specificity was determined at 100% using a set of 42 fusion negative samples. The limit of detection (LOD) was analyzed using serial dilutions to up to 3 log reduction (LR) using a the Seraseq Myeloid Fusion sample. The fusions were detected down to 1 LR. The reproducibility was tested using a positive fusion and Seraseq samples across three runs and was reported at 100%. Next, a small cohort of ALL samples (n=8) was included as part of this study to simultaneously evaluate DNA and RNA mutations. We detected pathogenic DNA variants in genes previously reported in ALL that included NOTCH1, PTEN, FLT3, IKZF1, JAK1, JAK2, KRAS, NF1, PAX5, U2AF1, TP53, and also RNA fusion BCR-ABL1, and the results were confirmed by an orthogonal NGS assay (NexCourse and RNA-Seqv1 for fusions). One sample carrying a BCR-ABL1 fusion (detected by RNA panel) also harbored mutations in IKZF1 in DNA (detected by DNA panel) that is reported as unfavorable prognostic biomarker for Ph-Like ALL demonstrating comprehensive panel could identify multiple variants within the same sample, demonstrating the advantage DNA+RNA testing has over the classical single gene FISH/RT-PCR testing for the efficient risk stratification and treatment in ALL patients. Conclusions: In this study, we demonstrated that the single tube TNA based NeoGenomics NGS assay can simultaneously detect the DNA and RNA biomarkers associated with ALL for improved diagnostic and prognostic recommendations. The single-tube assay for detection of both RNA fusions and DNA variants using the same sample could offer comprehensive and cost-effective solution for clinical laboratory test for ALL patient care. This is a promising approach that might be used as a dual DNA/RNA alterations detection on other hematological neoplasia. Disclosures Ramesh: Neo Genomics Laboratories: Current Employment. Koo: Neo Genomics Laboratories: Current Employment. Kang: Neo Genomics Laboratories: Current Employment. Ghosal: NeoGenomics Laboratories: Current Employment. Alarcon: NeoGenomics Laboratories: Current Employment. Gyuris: Neo Genomics Laboratories: Current Employment. Jung: NeoGenomics Laboratories, Inc.: Current Employment. Magnan: NeoGenomics Laboratories, Inc.: Current Employment. Nam: NeoGenomics Laboratories, Inc.: Current Employment. Thomas: NeoGenomics Laboratories, Inc.: Current Employment. Fabunan: NeoGenomics Laboratories, Inc.: Current Employment. Petersen: Neo Genomics Laboratories: Current Employment. Lopez-Diaz: NeoGenomics Laboratories, Inc.: Current Employment. Bender: NeoGenomics Laboratories, Inc.: Current Employment. Agersborg: NeoGenomics Laboratories, Inc.: Current Employment. Ye: Neo Genomics Laboratories: Current Employment. Funari: NeoGenomics Laboratories, Inc.: Current Employment.

Background: Paired-box Pax gene family protein 5 (PAX5)/B-cell specific activator protein (BSAP) is a transcription factor encoded by the PAX5 gene and has an essential role in B-cell differentiation and maturation. High PAX5 expression is detected ensures commitment to B-cell lineage. PAX5 is normally downregulated at the plasma cell stage of B-cell development. Complete or partial deletion of the PAX5 gene has been found as secondary event associated with BCR-ABL1 or TCF3-PBX1 fusions in Acute Lymphocytic Leukemia (ALL) cases. PAX5 expression is a diagnostic marker for B-cell lineage and may help quantify minimal residual disease in B-ALL. Lineage determination of leukemic blasts is most often performed by flow cytometry, but also by immunohistochemistry (IHC). Evaluation of PAX5 is most commonly available by IHC and is not widely performed by flow cytometry. In cases with limited specimen for evaluation or aberrant loss of some B-cell markers, determining quantitative levels of RNA from lineage-specific genes, such as PAX5, could be a valuable clinical diagnostic tool for ALL patients. Our existing single tube NGS based assay for simultaneous detection of DNA alterations and RNA fusions in heme malignancies from Total Nucleic Acid (TNA), can also be used to detect PAX5 gene expression through select exons enrichment along with a total of 213 genes. However, one of the current challenges for NGS-based gene expression profiling is to setup a threshold for overexpression. Here we developed a cutoff criterion for PAX5 overexpression and evaluated the performance of PAX5 gene expression analysis using the in-use heme assay and its potential use in clinical laboratory for cell lineage detection. Methods: RNA sequencing was performed on TNA extracted from ALL samples and from 32 healthy donors using partial anchored amplicon based (Qiagen, inc) heme NGS assay. PAX5 RNA expression was calculated by TPM (transcript per million) counts normalized to TPM of the house-keeping gene GUSB. A commercially available qRT-PCR assay was used as orthogonal method to confirm the gene expression. The expression call by NGS based on the normalized value was confirmed by a commercial qRT-PCR assay in house validated through serial dilutions of template for six log scale. The analytical cutoff was determined from normalized TPM calculation from 32 healthy volunteers following CLSI guideline (CLSI_EP17-A2) and evaluated the outcome with IHC positive /negative clinical samples (a CLIA validated assay). Further, we used the established cutoff to evaluate the sensitivity or specificity in cohort of ALL samples. Results: In this study we established the cutoff for PAX5 gene over-expression using the currently in-use heme NGS assay. First, a cutoff was established following the method in the CLSI guidelines and tested for sensitivity and specificity in the ALL sample cohort. PAX5 TPM normalization to GUSB or to the geometric mean of four house keeping genes (GUSB, PGD, RPL5 and RPL19) showed a strong correlation (R2>0.95), and GUSB was selected for further normalization since GUSB TPM values were most conserved across all the samples. Independent in-house evaluation for commercial qRT-PCR assay showed efficiency at 94.3 and 96% for GUSB and PAX5, respectively (with linearity R2>0.95), and been used to compare the NGS and IHC data as independent orthogonal assay. When a cohort of samples for Pax5 by IHC (positive and negative), a sensitivity at 67% and specificity at 100% were observed for the NGS based Pax5 detection. NGS results on the discordant samples were confirmed by qRT-PCR to have low RNA expression. Notably the discordant, IHC positive samples contained very low numbers of B cells. Alongside with other possible mechanisms of increased protein levels such as increased protein translation/increased protein stability could explain the discordance between RNA expression and the protein detection by IHC. Conclusions: In this study we demonstrate that NeoGenomics's (heme) NGS assay can be used for PAX5 gene over-expression analysis on ALL. The heme NGS is inexpensive and is already integrated in the benchwork workflow without adding extra burden and can be used as an objective quantification of PAX5 levels overcoming the challenges associated with the relative signal intensity biases in IHC testing. This type of RNA testing can be useful especially with specimens having limited material. Disclosures Ghosal: NeoGenomics Laboratories: Current Employment. Alarcon: NeoGenomics Laboratories: Current Employment. Koo: Neo Genomics Laboratories: Current Employment. Kang: Neo Genomics Laboratories: Current Employment. Ramesh: Neo Genomics Laboratories: Current Employment. Gyuris: Neo Genomics Laboratories: Current Employment. Jung: NeoGenomics Laboratories, Inc.: Current Employment. Thomas: NeoGenomics Laboratories, Inc.: Current Employment. Fabunan: NeoGenomics Laboratories, Inc.: Current Employment. Magnan: NeoGenomics Laboratories, Inc.: Current Employment. Nam: NeoGenomics Laboratories, Inc.: Current Employment. Petersen: Neo Genomics Laboratories: Current Employment. Lopez-Diaz: NeoGenomics Laboratories, Inc.: Current Employment. Bender: NeoGenomics Laboratories, Inc.: Current Employment. Agersborg: NeoGenomics Laboratories, Inc.: Current Employment. Ye: Neo Genomics Laboratories: Current Employment. Funari: NeoGenomics Laboratories, Inc.: Current Employment.